Journal of Engineering Science 04(1), 2013 11-22 ESTIMATING GROUNDWATER RECHARGE INTO A SHALLOW UNCONFINED AQUIFER IN BANGLADESH Sajal Kumar Adhikary 1* , Tanmay Chaki 2 , Md. Mahidur Rahman 1 and Ashim Das Gupta 3 1 Department of Civil Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh 2 Water Resources Planning Division, Institute of Water Modelling (IWM), Dhaka, Bangladesh 3 Water Engineering and Management, Asian Institute of Technology (AIT), Bangkok, Thailand Received 01 September 2012; Accepted 18 October 2012 ABSTRACT This paper presents a data conservative approach, in which quantitative groundwater recharge estimation in a shallow unconfined aquifer is interpreted in details by the analysis of observed precipitation and water level fluctuations records. Kushtia district in Bangladesh has been taken as a case study area based on the observed data and information. In the adopted state-of-the-art methodology used for this study, well-known water table fluctuation technique has been modified so that groundwater recharge in shallow aquifer can be estimated by using the least available data and information. Observed time series of precipitation and groundwater levels records at a few monitoring wells in the study area are the only data required to carry out the study. The approach illustrated in this paper can be useful in any initial level of assessment in groundwater studies. In addition, results can be applied as input data for developing numerical groundwater model for any groundwater resource investigation in the study area or similar drainage basins in Bangladesh. Keywords: Groundwater recharge, Kushtia, Precipitation, Unconfined aquifer, Water table fluctuation 1. INTRODUCTION Groundwater (GW) recharge is defined as the fraction of total precipitation falling into a drainage basin, which eventually reaches the water table in the saturation zone of an aquifer (Jukić and Jukić, 2004). It is a fundamental component of GW systems (Sanford, 2002), because information on GW recharge rates is often necessary for water resource management, inputs to regional GW models and predictions of climate change impacts (De Silva and Ruston, 2007). Thus, GW recharge is a critical hydrological parameter, which may need to be estimated at a variety of spatial and temporal scales depending on the application. Since GW recharge cannot be measured directly, it is often estimated by using the results of hydrogeologic and geologic investigations, hydro- meteorological data, observed discharges or GW level hydrographs (Jukić and Jukić, 2004). However, aquifer- scale recharge estimation is often required for water resource assessment and management, whereas local-scale recharge is critical to assessment of GW contamination from point sources. Estimation of GW recharge may be required on temporal scales ranging from days to thousands of years. As aquifers are depleted, recharge estimation have become more vital in determining appropriate levels of GW withdrawal. In addition, recharge estimation is becoming more important for contaminant transport, as aquifer management expands from cleanup of existing contamination to aquifer protection by delineation of areas of high recharge (Scanlon and Cook, 2002). Thus, understanding GW recharge and its accurate estimation is essential for the successful management of water resources and modelling fluid flow and transport of contaminants within the subsurface (Healy, 2010; Healy and Cook, 2002). Increasing demand for recharge estimation is forcing the researchers to develop approaches for building a more thorough understanding of aquifer recharging process and quantifying recharge rates that reduce uncertainties and increase confidence in recharge estimates (Scanlon and Cook, 2002). The fraction of precipitation that reaches the phreatic zone in an aquifer depends upon several factors including soil, topography, vegetation, and climate (Moon et al., 2004). Because of such influencing factors, determining the GW recharge into aquifers is one of the great challenges in almost all the GW studies (Korkmaz, 1988). Depending on the available hydrological data and information, numerous techniques for estimating GW recharge have been discussed intensively in the literatures (Venetics, 1971; Rushton and Ward, 1979; Caro and Eagleson, 1981; Johansson, 1987; Das Gupta and Paudyal, 1988; Korkmaz, 1988; Bekesi and McConchie, 1999; Arnold et al., 2000; Edmunds et al., 2002; Flint et al., 2002; Lewis and Walker, 2002; Scanlon et al., 2002; Jukić and Jukić, 2004; Moon et al., 2004; Anuraga et al., 2006; Rahman and Roehrig, 2006; Ruston et al., 2006; Sharda et al., 2006; Thomas and Tellam, 2006; Batelaan and de Smedt, 2007; Coes et al., 2007; De Silva and Ruston, 2007; Park and Parker, 2008; Martínez et al., 2009; Nziku et al., 2009; Izuka et al., 2010; Jie et al, 2011; Singh, 2011; Yin et al., 2011). However, most of these approaches often require much time and skill along with lots of * Corresponding author : [email protected]KUET @ JES, ISSN 2075-4914 / 04(1), 2013 JES an International Journal
12
Embed
ESTIMATING GROUNDWATER RECHARGE INTO A SHALLOW … … · Sajal Kumar Adhikary 1*, Tanmay Chaki 2, Md. Mahidur Rahman 1 and Ashim Das Gupta 3 1Department of Civil Engineering, Khulna
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Journal of Engineering Science 04(1), 2013 11-22
ESTIMATING GROUNDWATER RECHARGE INTO A SHALLOW UNCONFINED
AQUIFER IN BANGLADESH
Sajal Kumar Adhikary1*, Tanmay Chaki2, Md. Mahidur Rahman1 and Ashim Das Gupta3
1Department of Civil Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh 2Water Resources Planning Division, Institute of Water Modelling (IWM), Dhaka, Bangladesh
3Water Engineering and Management, Asian Institute of Technology (AIT), Bangkok, Thailand
Received 01 September 2012; Accepted 18 October 2012
ABSTRACT
This paper presents a data conservative approach, in which quantitative groundwater recharge estimation in a
shallow unconfined aquifer is interpreted in details by the analysis of observed precipitation and water level
fluctuations records. Kushtia district in Bangladesh has been taken as a case study area based on the observed
data and information. In the adopted state-of-the-art methodology used for this study, well-known water table
fluctuation technique has been modified so that groundwater recharge in shallow aquifer can be estimated by
using the least available data and information. Observed time series of precipitation and groundwater levels
records at a few monitoring wells in the study area are the only data required to carry out the study. The
approach illustrated in this paper can be useful in any initial level of assessment in groundwater studies. In
addition, results can be applied as input data for developing numerical groundwater model for any groundwater
resource investigation in the study area or similar drainage basins in Bangladesh.
Keywords: Groundwater recharge, Kushtia, Precipitation, Unconfined aquifer, Water table fluctuation
1. INTRODUCTION
Groundwater (GW) recharge is defined as the fraction of total precipitation falling into a drainage basin, which
eventually reaches the water table in the saturation zone of an aquifer (Jukić and Jukić, 2004). It is a fundamental
component of GW systems (Sanford, 2002), because information on GW recharge rates is often necessary for
water resource management, inputs to regional GW models and predictions of climate change impacts (De Silva
and Ruston, 2007). Thus, GW recharge is a critical hydrological parameter, which may need to be estimated at a
variety of spatial and temporal scales depending on the application. Since GW recharge cannot be measured
directly, it is often estimated by using the results of hydrogeologic and geologic investigations, hydro-
meteorological data, observed discharges or GW level hydrographs (Jukić and Jukić, 2004). However, aquifer-
scale recharge estimation is often required for water resource assessment and management, whereas local-scale
recharge is critical to assessment of GW contamination from point sources. Estimation of GW recharge may be
required on temporal scales ranging from days to thousands of years. As aquifers are depleted, recharge
estimation have become more vital in determining appropriate levels of GW withdrawal. In addition, recharge
estimation is becoming more important for contaminant transport, as aquifer management expands from cleanup
of existing contamination to aquifer protection by delineation of areas of high recharge (Scanlon and Cook,
2002). Thus, understanding GW recharge and its accurate estimation is essential for the successful management
of water resources and modelling fluid flow and transport of contaminants within the subsurface (Healy, 2010;
Healy and Cook, 2002). Increasing demand for recharge estimation is forcing the researchers to develop
approaches for building a more thorough understanding of aquifer recharging process and quantifying recharge
rates that reduce uncertainties and increase confidence in recharge estimates (Scanlon and Cook, 2002).
The fraction of precipitation that reaches the phreatic zone in an aquifer depends upon several factors including
soil, topography, vegetation, and climate (Moon et al., 2004). Because of such influencing factors, determining
the GW recharge into aquifers is one of the great challenges in almost all the GW studies (Korkmaz, 1988).
Depending on the available hydrological data and information, numerous techniques for estimating GW recharge
have been discussed intensively in the literatures (Venetics, 1971; Rushton and Ward, 1979; Caro and Eagleson,
1981; Johansson, 1987; Das Gupta and Paudyal, 1988; Korkmaz, 1988; Bekesi and McConchie, 1999; Arnold et
al., 2000; Edmunds et al., 2002; Flint et al., 2002; Lewis and Walker, 2002; Scanlon et al., 2002; Jukić and Jukić,
2004; Moon et al., 2004; Anuraga et al., 2006; Rahman and Roehrig, 2006; Ruston et al., 2006; Sharda et al.,
2006; Thomas and Tellam, 2006; Batelaan and de Smedt, 2007; Coes et al., 2007; De Silva and Ruston, 2007;
Park and Parker, 2008; Martínez et al., 2009; Nziku et al., 2009; Izuka et al., 2010; Jie et al, 2011; Singh, 2011;
Yin et al., 2011). However, most of these approaches often require much time and skill along with lots of